We will refine our three-dimensional modifiable computer models and reconstruction algorithm, and develop a compensation algorithm and other algorithms to improve the resolution and accuracy of the electrical impedance technique. We will design, construct, and test a matrix of electrodes, and a measurement and control circuitry. We will interface these to a microcomputer system that does data acquisition, impedance image reconstruction, and image display. We will construct physical models to test both system hardware and software. We will determine the correlation between physical models and reconstructed impedance images. We will assess the feasibility of the electrical impedance technique in medical body imaging as a new imaging modality and determine whether clinical applications of this developed instrument can be justified. The electrical impedance imaging technique is potentially complementary to existing X-ray transmission and emission as well as ultrasound and other techniques, because it uses different imaging source, it produces images based on each region's impedance value, and it might become a new imaging modality. For example, it may supplement X-ray CT scanner in various ways. It could reduce the overall exposure of the patient to hazardous X-ray radiation, because the use of high-frequency (greater than 100 kHz), low-level (less than 10 mA) current is proven to be safe. Electrical impedance imaging can help to image organs such as the lungs that are difficult to image with X-ray or ultrasonic CT scanners. It could monitor the pathological impedance changes in small regions within the torso and measure lung water and lung blood volume in a variety of clinical and research situations, because the conductivity of liquid in the lung is about 20 times that of the normal lung. With improved resolution and specificity, we should be able to identify solid tumor for the same reason. Thus, the instrument, once developed, could assist in diagnosis of many abnormalities within the torso safely and noninvasively.